To address the above two challenges, we propose a novel SAF network composed of Speech Decomposition Network (SDN), Auxiliary Feature Network (AFN) and Feature Transformation Network (FTN), which we call SAFN in brief. Firstly, in order to adapt to the speaker-independent case, we explore a SDN inspired by the idea of speech synthesis [1]} to obtain the personalized speech features. Then, to further improve the performance of AAI, we propose a novel AFN to estimate the lip auxiliary features as the prior information from the personalized speech features. Then, we design a FTN to generate feature pairs by transforming the personalized speech features and the lip auxiliary features. Last but not least, though AAI is not an one-to-one maping task (i.e., different articulatory movements may correspond to the same speech), this problem can be alleviated by ensuring the smoothness of the articulatory movement on consecutive frames. An overview of our SAFN is shown in Fig. REF .
